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kroq86

Runtime Copilot MCP Server

by kroq86

demo_explain_semantic_failure

Run a traced semantic-corruption flow to identify and explain validation failures in your data pipeline.

Instructions

Run a traced semantic-corruption flow and explain the failed validation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
root_dirNo./tests/artifacts/mcp/explain_demo_semantic_failure
tableNoorders
customer_idNo
trace_db_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states the tool runs a flow and explains validation, but does not disclose side-effects (e.g., data mutation), resource requirements, or whether it is read-only. The agent cannot infer safety or expected behavior beyond the basic action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but lacks structure. It covers the basic purpose without elaboration, leaving out necessary details. While compact, it does not earn its brevity by providing critical information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (4 parameters, no param docs, no annotations), the description is incomplete. Although an output schema exists, the missing parameter semantics and behavioral traits leave significant gaps for correct invocation and interpretation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the description does not explain any of the four parameters (root_dir, table, customer_id, trace_db_path). The agent receives no guidance on how these inputs affect the tool's behavior, making parameter selection opaque.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies the action ('run a traced semantic-corruption flow') and outcome ('explain the failed validation'), providing a clear verb and resource. It implicitly distinguishes from sibling demo tools that handle concurrency or idempotency failures, though the jargon might reduce clarity for an AI agent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no guidance on when to use this tool versus alternatives like demo_explain_concurrency_failure_storm or demo_explain_idempotency_conflict. There is no mention of prerequisites, context, or scenarios where this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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